Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint=true, and the description is consistent with that. It adds valuable context beyond the annotations: the computation basis (PM2.5 vs 85-day baseline), data source (Open-Meteo), refresh cadence (daily), and the Gold tier requirement for history. This enriches the agent's understanding without contradicting structured data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact yet information-dense. The first sentence packs the core functionality and output fields, the second gives explicit usage scenarios, and the final 'Updates: daily' is a succinct update frequency note. No unnecessary words or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description lists the return fields (mean_city_z, cities_analyzed, WHO-guideline exceedance count/pct, hottest/coolest extremes) and explains the score's meaning and refresh policy. It also covers the optional history parameter. Minor gaps remain, such as the exact JSON structure, but overall it provides sufficient context for correct tool selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for the single optional parameter 'days'. The schema's description fully explains its purpose and the Gold tier requirement, so the tool description does not need to add more. The description itself does not contribute additional parameter semantics, hence the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function with a specific verb and resource: 'Returns a 0-100 global air-quality health load score' based on city PM2.5 means vs an 85-day baseline. It also lists the output fields, making it unambiguous and distinct from other tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says when to call the tool: 'Call when the user asks about global air pollution, PM2.5 spikes, wildfire-smoke health load, or WHO guideline breaches...' It does not, however, mention when not to use it or name alternatives such as the sibling tool adw.air_quality_risk, so it falls short of a perfect score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.